Bioelectrical impedance analysis of body composition and survival in patients with heart failure

Abstract

Background: Studies have shown that higher body mass index (BMI) is associated with improved prognosis in heart failure (HF), and this is often termed the obesity paradox.Hypothesis: Analysis of body composition may reveal that muscle mass rather than adipose tissue accounts for the obesity paradox.Methods: Bioelectrical impedance analysis of body composition in 359 outpatients with HF was performed using an In Body 520 body composition scale (Biospace Inc., California). Body fat and lean mass were indexed by height (m 2 ). The cohort was stratified by median fat and lean mass indexed by height. Results:The mean age of patients studied was 56 AE 14; mean left ventricular ejection fraction was 38 AE 16%. Patients with higher indexed body fat mass had improved 5-year survival over patients with lower indexed body fat mass (90.2% vs 80.1%, P = 0.008). There was also improved survival in patients with high vs low indexed lean body mass (89.3% vs 80.9%, P = 0.036). On multivariable analysis, higher indexed body fat mass, but not lean body mass, was independently associated with improved survival (HR 0.89, per kg/m 2 increase in indexed body fat mass, P = 0.044); however, this was attenuated after adjustment for diabetes. The combination of low lean with low-fat mass was independently associated with poor prognosis.Conclusions: Our data suggest that higher fat mass-and to a lesser extent higher lean mass-is associated with improved outcomes in HF. Further investigations of specific components of body composition and outcomes in HF are warranted.

Discriminating sarcopenia in overweight/obese male patients with heart failure: the influence of body mass index

“…10 Although BMI is high, this protective effect of overweight/obesity in these patients may be abolished in the presence of decreased lean mass and increased fat mass. 10,11 Moreover, increases in BMI cannot detect the regional body fat mass distribution, especially visceral fat that has been associated with mortality in these patients. 22 Furthermore, the protective effect of higher BMI should be considered with markers of functional capacity, once the obesity paradox has been described to be more significant in patients with lower cardiorespiratory fitness.…”

“…Paradoxically, although obesity increases the risk of HF, obese patients with HF with reduced ejection fraction (HFrEF) may have lower mortality rate than patients with healthy standard body mass index (BMI; 18.5–24.99 kg/m 2 ) . However, the protective effect of higher BMI is abolished in the presence of reduced lean mass and increased fat mass …”

“…9 However, the protective effect of higher BMI is abolished in the presence of reduced lean mass and increased fat mass. 10,11 To overcome the limitation of ALM/height 2 (Baumgartner's method) to define sarcopenia in overweight/obese patients, other definitions have been suggested. For instance, the residuals of a linear regression derived from adjusting lean mass for height and fat mass (Newman's method) seem to be more accurate in patients with high BMI, mainly composed of fat mass.…”

Bioelectrical impedance analysis for perioperative water management in adult cardiovascular valve disease surgery

“…BIA has been applied for the water management of hemodialysis patients and also recently for the water management of heart failure and cardiac surgery patients [16][17][18][19][20][21][22].…”

“…According to several reports on BIA in clinical studies, the phase angle (PA), one type of BIA readout, shared a correlation with a nutrition marker and was a potential postoperative risk marker for cardiac surgery [12][13][14][15]. Studies on the differences in water behavior with some kinds of diuretics found that one readout of BIA, the edema index (EI), being the ratio of extracellular water to total body water, can predict the amount of fluid reduction needed for patients with acute heart failure and chronic renal disease [16][17][18][19][20][21][22]. We hypothesized that perioperative water management could be improved by a better understanding of perioperative water behavior through BIA.…”